The obsession with removing friction is often wrong. When users have low intent or understanding, the goal isn't to speed them up but to build their comprehension of your product's value. If software asks you to make a decision you don't understand, it makes you feel stupid, which is the ultimate failure.

Instead of focusing solely on conversion rates, measure 'engagement quality'—metrics that signal user confidence, like dwell time, scroll depth, and journey progression. The philosophy is that if you successfully help users understand the content and feel confident, conversions will naturally follow as a positive side effect.

As businesses scale, they often abandon the scrappy, creative tactics that sparked their initial growth. To combat rising ad costs and channel fatigue, intentionally revisit these early, 'unscalable' activities. Re-injecting that fun, different energy can generate the 'free memories' and reach needed for the next growth phase.

As a company grows, its old operational systems and processes ('plumbing') become obsolete. True scaling is not about addition; it's about reinvention. This involves systematically removing outdated processes designed for a smaller scale and replacing them entirely.

Instead of treating all channels equally, identify which customer segments (e.g., brand advertisers) are best served by which channels (e.g., TV screens). Shifting demand accordingly can unlock massive growth by optimizing the entire portfolio and increasing customer ROI.

After reaching scale, a product's dormant user base is a massive growth opportunity. Activating these users requires designing specific return experiences, like Duolingo’s proficiency tests, which can be a bigger lever than new user acquisition.

When handed a specific solution to build, don't just execute. Reverse-engineer the intended customer behavior and outcome. This creates an opportunity to define better success metrics, pressure-test the underlying problem, and potentially propose more effective solutions in the future.

Figma learned that removing issues preventing users from adopting the product was as important as adding new features. They systematically tackled these blockers—often table stakes features—and saw a direct, measurable improvement in retention and activation after fixing each one.

Avoid the 'settings screen' trap where endless customization options cater to a vocal minority but create complexity for everyone. Instead, focus on personalization: using behavioral data to intelligently surface the right features to the right users, improving their experience without adding cognitive load for the majority.